关键词: 立体匹配, 最小生成树, 无纹理区域, 边缘信息

Abstract:

To solve the problem of mismatching in the textureless and edge regions of the non-local algorithm based on minimum spanning tree, an improved cost measurement and color and edge fusion non-local stereo matching algorithm is proposed. Firstly, the cost function based on color-gradient is reconstructed to improve the matching effectiveness in textureless regions. Secondly, an adaptive edge weight function based on image color and edge information is proposed, and the weight is used to construct the tree structure for cost aggregation. The final disparity map is obtained after disparity computation and non-local disparity refinement. The experimental results on the Middlebury dataset show that the proposed algorithm achieves good matching results in both the textureless and edge regions, and improves the disparity effectively.

Key words: stereo matching, minimum spanning tree, textureless region, edge information